Article

Six Challenges for Human-AI Co-learning

Authors:

Karel van den Bosch,

Tjeerd Schoonderwoerd,

Romy Blankendaal,

Mark NeerincxAuthors Info & Claims

Adaptive Instructional Systems: First International Conference, AIS 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Orlando, FL, USA, July 26–31, 2019, Proceedings

Pages 572 - 589

https://doi.org/10.1007/978-3-030-22341-0_45

Published: 26 July 2019 Publication History

Abstract

The increasing use of ever-smarter AI-technology is changing the way individuals and teams learn and perform their tasks. In hybrid teams, people collaborate with artificially intelligent partners. To utilize the different strengths and weaknesses of human and artificial intelligence, a hybrid team should be designed upon the principles that foster successful human-machine learning and cooperation. The implementation of the identified principles sets a number of challenges. Machine agents should, just like humans, have mental models that contain information about the task context, their own role (self-awareness), and the role of others (theory of mind). Furthermore, agents should be able to express and clarify their mental states to partners. In this paper we identify six challenges for humans and machines to collaborate in an adaptive, dynamic and personalized fashion. Implications for research are discussed.

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Do HBrachman MDugan CJohnson JLauer JRai PPan Q(2024)Grounding with Structure: Exploring Design Variations of Grounded Human-AI Collaboration in a Natural Language InterfaceProceedings of the ACM on Human-Computer Interaction10.1145/36869028:CSCW2(1-27)Online publication date: 8-Nov-2024
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Published In

cover image Guide Proceedings

Adaptive Instructional Systems: First International Conference, AIS 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Orlando, FL, USA, July 26–31, 2019, Proceedings

Jul 2019

647 pages

ISBN:978-3-030-22340-3

DOI:10.1007/978-3-030-22341-0

Editors:
Robert A. Sottilare
Soar Technology, Inc.,, Orlando, FL, USA
,
Jessica Schwarz
Fraunhofer FKIE, Wachtberg, Germany

© Springer Nature Switzerland AG 2019.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 26 July 2019

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Cited By

Do HBrachman MDugan CJohnson JLauer JRai PPan Q(2024)Grounding with Structure: Exploring Design Variations of Grounded Human-AI Collaboration in a Natural Language InterfaceProceedings of the ACM on Human-Computer Interaction10.1145/36869028:CSCW2(1-27)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686902
Wang ZShen LKuang EZhang SFan M(2024)Exploring the Impact of Artificial Intelligence-Generated Content (AIGC) Tools on Social Dynamics in UX CollaborationProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3660703(1594-1606)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3643834.3660703
Breideband TBush JChandler CChang MDickler RFoltz PGanesh ALieber RPenuel WReitman JWeatherley JD'Mello S(2023)The Community Builder (CoBi): Helping Students to Develop Better Small Group Collaborative Learning SkillsCompanion Publication of the 2023 Conference on Computer Supported Cooperative Work and Social Computing10.1145/3584931.3607498(376-380)Online publication date: 14-Oct-2023
https://dl.acm.org/doi/10.1145/3584931.3607498
Kalff EMaaiveld TSchadd MVoogd JWeyland L(2023)Survey on Sensing, Modelling and Reasoning Aspects in Military Autonomous SystemsModelling and Simulation for Autonomous Systems10.1007/978-3-031-71397-2_17(263-284)Online publication date: 17-Oct-2023
https://dl.acm.org/doi/10.1007/978-3-031-71397-2_17
Hu XTwidale M(2023)A Scoping Review of Mental Model Research in HCI from 2010 to 2021HCI International 2023 – Late Breaking Papers10.1007/978-3-031-48038-6_7(101-125)Online publication date: 23-Jul-2023
https://dl.acm.org/doi/10.1007/978-3-031-48038-6_7

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